Related Experiment Video
Updated: Aug 5, 2026
09:44
Automated Analysis of a Nematode Population-based Chemosensory Preference Assay
Published on: July 13, 2017
Manual and Fully Automated Chemotaxis-Based Cancer Screening Yield Equivalent Performance: A Nine-Month Real-World,
Hideyuki Hatakeyama1, Masayo Morishita1, Hirotaka Oshida1
1HIROTSU BIO SCIENCE Inc., 22F The New Otani Garden Court, 4-1 Kioi-cho, Chiyoda-ku, Tokyo 102-0094, Japan.
Biomedicines
|July 28, 2026
Summary
Automation of the N-NOSE cancer screening test using Caenorhabditis elegans chemotaxis maintains analytical performance. Real-world data confirm the automated Chemotaxis Scoring Apparatus (CSA) reliably discriminates cancer from non-cancer urine, supporting large-scale validation.
Area of Science:
- Biotechnology and Biomedical Engineering
- Cancer Diagnostics and Screening
- Nematode-based Assays
Background:
- The N-NOSE test is a non-invasive, urine-based assay utilizing Caenorhabditis elegans chemotaxis to detect cancer-associated volatile organic compounds.
- Scaling the N-NOSE test from manual to automated, high-throughput clinical service necessitates validation of analytical performance under operational conditions.
Purpose of the Study:
- To compare the analytical performance of a manual N-NOSE workflow with a fully automated workflow using the Chemotaxis Scoring Apparatus (CSA).
- To assess whether automation compromises the discriminative ability of the N-NOSE test in a real-world clinical laboratory setting.
Main Methods:
- A nine-month, side-by-side comparison of manual and automated N-NOSE workflows was conducted under routine clinical laboratory conditions.
- The manual workflow involved technicians at the Fukuoka R&D Center, while the automated workflow utilized the CSA at the Tokyo Testing Center.
- Both workflows processed quality control samples, including synthetic volatile organic compound (VOC) standards and biobank-derived urine, to measure chemotaxis index (CI) and risk scores.
Main Results:
- Both manual and automated workflows demonstrated highly significant and quantitatively comparable separation between positive and negative controls (p < 0.0001).
- Standardized separation metrics (Cohen's d) were concordant across both workflows, indicating no meaningful difference in discriminative performance.
- The CSA risk score, a transformation of the CI, showed analytical equivalence to the manual process, confirming the reliability of the automated system.
Conclusions:
- Automation of the N-NOSE assay does not compromise its ability to discriminate between cancer and non-cancer urine samples.
- The study provides real-world evidence supporting the validity, reproducibility, and reliability of the automated N-NOSE testing process for large-scale validation.
